Method and system for managing multiple supply chains

ABSTRACT

The present disclosure discloses a supply chain management system that can estimate manufactured item delivery times at a facility, manufactured item costs or prices, and dynamically control supply chain performance.

CROSS REFERENCE TO RELATED APPLICATION

The present application claims the benefits of U.S. ProvisionalApplication Ser. Nos. 61/668,282, filed Jul. 5, 2012; 61/716,960, filedOct. 22, 2012, and 61/750,184, filed Jan. 8, 2013, all entitled “Methodand System for Controlling Supply Chains”, and 61/800,197, filed Mar.15, 2013, entitled “Method and System for Managing Supply Chains”, eachof which is incorporated herein by this reference in its entirety.

FIELD

The disclosure relates generally to automated systems for productmanagement and particularly to automated systems for controlling and/ormanaging supply chains.

BACKGROUND

The traditional structure of the business supply chain, which viewedsupply chain management as a chain of events, is evolving, in responseto the ever-complicated logistics of modern trade, commerce andcommunications, towards viewing supply chain management as athree-dimensional model. In other words, organizations no longer viewsupply networks as a linear relationship between raw materials anddistributors. Rather, today's supply web resembles a three-dimensionalconstruct, complete with a variety of suppliers, tiers andintermediaries that serve to fill in for one another in the event of adisruption.

Increasingly, how well a supply web creates and shares information notonly defines how well the web holds together, how efficiently itoperates, and how much value it adds but also determines the success orfailure—as a group—of the manufacturing venture. Companies need to sharesupply metrics, timelines, demand and capacity data to enable the supplynetwork to develop a common and aligned set of objectives, which canprotect it against commodity pressures, volatility and individualfailures. Sharing information can speed up supply chains whilemitigating the inherent risks in doing so. This new model, with costmanagement at its core, can capture decades of best practices in aunified strategy for a new generation of companies and managers.

Essential to the practices of supply chains is the establishment ofmaterial control through a combination of material control towers thatdictate, to suppliers, price, terms, and supply requirements.

Although significant advances have been made towards establishing athree-dimensional supply chain by companies such as E2open™, GT Nexus™,and Resilinc™, problems remain. Many three-dimensional supply chains arefairly rigid and unable to respond dynamically to, let alone anticipate,adverse events. This can cause disruption in the supply chain andconcomitant interruptions in the product distribution chain.

SUMMARY

These and other needs are addressed by the various aspects, embodiments,and/or configurations of the present disclosure. The present disclosurediscloses a supply chain management system that can estimatemanufactured item delivery times at a facility, manufactured item costsor prices, and dynamically control supply chain performance.

A system for monitoring multiple supply chains for different products(with performance information collected for each monitored supply chainbeing confidential to the respective monitored supply chain and beingstored in a common database) can include a microprocessor executablesecurity module, method, and/or instructions to receive a query, commandand/or request from a requestor to perform an operation with respect toa set of data and/or data structures in the database, modify the query,command and/or request to conform to a security definition, and use themodified query, command and/or request to perform the operation.

The database is commonly not partitioned logically into distinct andindependent parts corresponding to different monitored supply chains,and the data and/or data structures for different monitored supplychains are commonly commingled in the database.

The query, command and/or request can be modified by the securitymodule, method, and/or instructions to reflect a supply chain roleand/or an identity of an enterprise and/or organization associated withthe requestor, whereby the data and/or data structures impacted by thequery, command, and/or request are limited to those relating to thesupply chain role and/or identity of the enterprise and/or organizationassociated with the requestor.

The security module, method, and/or instructions can determine whetherthe requestor has permission to use an application associated with theoperation and, when the requestor is without permission to use theapplication, deny the query, command, and/or request.

The query, command, and/or request can be required to pass through anapplication programming interface prior to performance of the operation.

The security module, method, and/or instructions can determine whetherthe requestor has permission to use the application programminginterface and/or whether the query, command and/or request conforms tothe requirements of the application programming interface and, when therequestor is without permission to use the application programminginterface and/or when the query, command, and/or request fails toconform to the requirements of the application programming interface,deny the query, command, and/or request.

The requestor can be required to have a specified role and relationshipto a selected monitored supply chain enterprise and/or organizationbefore the operation can be performed.

A datum and/or datum structure of the set of data and/or data structurescan have different states, wherein an action must be performed to changethe state of the datum and/or datum structure, each action can only beperformed when the requestor has a permission to perform the action, andone of the different states has plural sub-states that must be performedbefore the state can change.

The supply chain management system can perform one or more of thefollowing tasks, functions, and/or operations:

(a) Track historic performance of a supply chain;

(b) Anticipate and/or quickly identify potentially disruptive event(s)and mitigate the adverse impact of the potentially disruptive event(s)on the supply chain;

(c) Analyze supply chains to identify cost inefficiencies, bottlenecks,and unnecessary performance delays;

(d) Recommend and/or implement solutions for the identified costinefficiencies, bottlenecks, and unnecessary performance delays;

(e) Monitor the performance of a supply chain in light of distributionchain requirements or objectives to identify potential violations orshortfalls; and

(f) Recommend and/or implement solutions to avoid or mitigate theidentified potential violations or shortfalls.

Supply chain performance metrics are commonly not calculated, insubstantial real time, based on the performance information collectedfrom the monitored supply chains.

All or parts of the supply chain management system can be executed onone or more computers and typically is stored as microprocessorexecutable instructions on a computer readable medium.

The present disclosure can provide a number of advantages depending onthe particular aspect, embodiment, and/or configuration. The supplychain management system can, particularly for vertically integratedsupply chains, more effectively and efficiently control suppliers,prices, product supply, and other terms, generate faster material turnsor velocities, increase profit, enable leaner manufacturing andlogistics operations, and reduce waste when compared to a supply chainwithout the supply chain management system. It can more effectivelyconsider the impact of unanticipated or “black swan” events, includingnatural and manmade disasters, by monitoring news sources, lawenforcement and military authorities, among others, and preciselymapping tier 1, 2, 3, and 4 facilities. It can effectively assess thesensitivity of the supply chain to various internal and external events.It can assess the risk of having a particular product or productcomponent available at a selected location at a selected price or cost.It can enable greater levels of collaboration not only among the varioustiers but also within tiers. It can enable more effective management ofmultiple sources, within a given tier, even for legally distinct,competitive entities. The system's combination of cloud tools, operatingmodels, and risk management logic can create new, more profitable andeffective business practices in three-dimensional supply chains.

These and other advantages will be apparent from the disclosure.

The phrases “at least one”, “one or more”, and “and/or” are open-endedexpressions that are both conjunctive and disjunctive in operation. Forexample, each of the expressions “at least one of A, B and C”, “at leastone of A, B, or C”, “one or more of A, B, and C”, “one or more of A, B,or C” and “A, B, and/or C” means A alone, B alone, C alone, A and Btogether, A and C together, B and C together, or A, B and C together.

The term “a” or “an” entity refers to one or more of that entity. Assuch, the terms “a” (or “an”), “one or more” and “at least one” can beused interchangeably herein. It is also to be noted that the terms“comprising”, “including”, and “having” can be used interchangeably.

“Advanced planning and scheduling” (also referred to as APS and advancedmanufacturing) refers to a manufacturing management process by which rawmaterials and production capacity are substantially optimally allocatedto meet demand. APS is especially well-suited to environments wheresimpler planning methods cannot adequately address complex trade-offsbetween competing priorities. Production scheduling can be verydifficult due to the (approximately) factorial dependence of the size ofthe solution space on the number of items/products to be manufactured.

“Automatic” and variations thereof, as used herein, refers to anyprocess or operation done without material human input when the processor operation is performed. However, a process or operation can beautomatic, even though performance of the process or operation usesmaterial or immaterial human input, if the input is received beforeperformance of the process or operation. Human input is deemed to bematerial if such input influences how the process or operation will beperformed. Human input that consents to the performance of the processor operation is not deemed to be “material”.

“Computer-readable medium” as used herein refers to any tangible andnon-transient storage and/or transmission medium that participate inproviding instructions to a processor for execution. Such a medium maytake many forms, including but not limited to, non-volatile media,volatile media, and transmission media and includes without limitationrandom access memory (“RAM”), read only memory (“ROM”), and the like.Non-volatile media includes, for example, NVRAM, or magnetic or opticaldisks. Volatile media includes dynamic memory, such as main memory.Common forms of computer-readable media include, for example, a floppydisk (including without limitation a Bernoulli cartridge, ZIP drive, andJAZ drive), a flexible disk, hard disk, magnetic tape or cassettes, orany other magnetic medium, magneto-optical medium, a digital video disk(such as CD-ROM), any other optical medium, punch cards, paper tape, anyother physical medium with patterns of holes, a RAM, a PROM, and EPROM,a FLASH-EPROM, a solid state medium like a memory card, any other memorychip or cartridge, a carrier wave as described hereinafter, or any othermedium from which a computer can read. A digital file attachment toe-mail or other self-contained information archive or set of archives isconsidered a distribution medium equivalent to a tangible storagemedium. When the computer-readable media is configured as a database, itis to be understood that the database may be any type of database, suchas relational, hierarchical, object-oriented, and/or the like.Accordingly, the disclosure is considered to include a tangible storagemedium or distribution medium and prior art-recognized equivalents andsuccessor media, in which the software implementations of the presentdisclosure are stored. Computer-readable storage medium excludestransient storage media, particularly electrical, magnetic,electromagnetic, optical, magneto-optical signals.

“Critical path method” refers to an algorithm for scheduling a set ofproject activities. CPM constructs a model of the project that includesthe following: (a) a list of all activities required to complete theproject (typically categorized within a work breakdown structure), (b)the time (duration) that each activity will take to completion, and (c)the dependencies between the activities. Using these values, CPMcalculates the longest path of planned activities to the end of theproject, and the earliest and latest that each activity can start andfinish without making the project longer. This process determines whichactivities are “critical” (i.e., on the longest path) and which have“total float” (i.e., can be delayed without making the project longer).In project management, a critical path is the sequence of projectnetwork activities which add up to the longest overall duration. Thisdetermines the shortest time possible to complete the project. Any delayof an activity on the critical path directly impacts the planned projectcompletion date (i.e. there is no float on the critical path). A projectcan have several, parallel, near critical paths. An additional parallelpath through the network with the total durations shorter than thecritical path is called a sub-critical or non-critical path.

A “database” is an organized collection of data held in a computer. Thedata is typically organized to model relevant aspects of reality (forexample, the availability of specific types of inventory), in a way thatsupports processes requiring this information (for example, finding aspecified type of inventory). The organization schema or model for thedata can, for example, be hierarchical, network, relational,entity-relationship, object, document, XML, entity-attribute-valuemodel, star schema, object-relational, associative, multidimensional,multivalue, semantic, and other database designs. Database typesinclude, for example, active, cloud, data warehouse, deductive,distributed, document-oriented, embedded, end-user, federated, graph,hypertext, hypermedia, in-memory, knowledge base, mobile, operational,parallel, probabilistic, real-time, spatial, temporal,terminology-oriented, and unstructured databases.

“Database management systems” (DBMSs) are specially designedapplications that interact with the user, other applications, and thedatabase itself to capture and analyze data. A general-purpose databasemanagement system (DBMS) is a software system designed to allow thedefinition, creation, querying, update, and administration of databases.Well-known DBMSs include MySQL™, PostgreSQL™, SQLite™, Microsoft SQLServer™ Microsoft Access™, Oracle™, SAP™, dBASE™, FoxPro™, and IBM DB2™.A database is not generally portable across different DBMS, butdifferent DBMSs can inter-operate by using standards such as SQL andODBC or JDBC to allow a single application to work with more than onedatabase.

“Determine”, “calculate” and “compute,” and variations thereof, as usedherein, are used interchangeably and include any type of methodology,process, mathematical operation or technique.

An “enterprise” refers to a business and/or governmental organization,such as a corporation, partnership, joint venture, agency, militarybranch, and the like.

“Enterprise resource planning” or ERP systems integrate internal andexternal management information across an entire organization, embracingfinance/accounting, manufacturing, sales and service, customerrelationship management, and the like. ERP systems automate thisactivity with an integrated software application. The purpose of ERP isto facilitate the flow of information between all business functionsinside the boundaries of the organization and manage the connections tooutside stakeholders.

“Manufacturing process management” or MPM is a collection oftechnologies and methods used to define how products are to bemanufactured. MPM differs from ERP/MRP, which is used to plan theordering of materials and other resources, set manufacturing schedules,and compile cost data. A cornerstone of MPM is the central repositoryfor the integration of all these tools and activities aids in theexploration of alternative production line scenarios; making assemblylines more efficient with the aim of reduced lead time to productlaunch, shorter product times and reduced work in progress (WIP)inventories as well as allowing rapid response to product or productchanges.

“Material requirements planning” or MRP is a production planning andinventory control system used to manage manufacturing processes. MostMRP systems are software-based. An MRP system is intended tosimultaneously meet three objectives, namely ensure materials areavailable for production and products are available for delivery tocustomers, maintain the lowest possible material and product levels instore, and plan manufacturing activities, delivery schedules andpurchasing activities.

“Means” as used herein shall be given its broadest possibleinterpretation in accordance with 35 U.S.C., Section 112, Paragraph 6.Accordingly, a claim incorporating the term “means” shall cover allstructures, materials, or acts set forth herein, and all of theequivalents thereof. Further, the structures, materials or acts and theequivalents thereof shall include all those described in the summary ofthe invention, brief description of the drawings, detailed description,abstract, and claims themselves.

“Module” as used herein refers to any known or later developed hardware,software, firmware, artificial intelligence, fuzzy logic, or combinationof hardware and software that is capable of performing the functionalityassociated with that element. Also, while the disclosure is presented interms of exemplary embodiments, it should be appreciated that individualaspects of the disclosure can be separately claimed.

An “original equipment manufacturer”, or OEM, manufactures product orcomponents that are purchased by another enterprise and retailed underthat purchasing enterprise's brand name. OEM refers to an enterprisethat originally manufactured the product. When referring to automotiveparts for instance, OEM designates a replacement part made by themanufacturer of the original part.

“Queueing theory” refers to algorithms for characterizing or definingthe behavior of queues. Queueing theory is generally considered a branchof operations research because the results are often used when makingbusiness decisions about the resources needed to provide service. Aqueueing model based on the Poisson process and its companionexponential probability distribution often meets these two requirements.A Poisson process models random events (such as a customer arrival, arequest for action from a web server, or the completion of the actionsrequested of a web server) as emanating from a memoryless process. Thatis, the length of the time interval from the current time to theoccurrence of the next event does not depend upon the time of occurrenceof the last event. In the Poisson probability distribution, the observerrecords the number of events that occur in a time interval of fixedlength. In the (negative) exponential probability distribution, theobserver records the length of the time interval between consecutiveevents. In both, the underlying physical process is memoryless. Examplesof queueing theory functions or principals include BCMP network, Buzen'salgorithm, Ehrenfest model, fork join queue, Gordon-Newell network,Jackson network, Little's law, Markovian arrival processes,Pollaczek-Khinchine formula, quasireversibility, random early detection,renewal theory, the Poisson process, and the like. Models based on thePoisson process often respond to inputs from the environment in a mannerthat mimics the response of the system being modeled to those sameinputs. The analytically tractable models that result yield bothinformation about the system being modeled and the form of theirsolution. Even a queueing model based on the Poisson process that does arelatively poor job of mimicking detailed system performance can beuseful. The fact that such models often give “worst-case” scenarioevaluations appeals to system designers who prefer to include a safetyfactor in their designs. The form of the solution of models based on thePoisson process often provide insight into the form of the solution to aqueueing problem whose detailed behavior is poorly mimicked. As aresult, queueing models are frequently modeled as Poisson processesthrough the use of the exponential distribution.

“Scheduling algorithms” refer to production scheduling and includesforward and/or backward scheduling. Forward scheduling is planning thetasks from the date resources become available to determine the shippingdate or the due date. Backward scheduling is planning the tasks from thedue date or required-by date to determine the start date and/or anychanges in capacity required. Stochastic scheduling algorithms includeeconomic lot scheduling problem (which is concerned with scheduling theproduction of several products on a single machine in order to minimizethe total costs incurred (which include setup costs and inventoryholding costs) and the economic production quantity model (whichdetermines the quantity a enterprise and/or organization and/or retailershould order to minimize the total inventory costs by balancing theinventory holding cost and average fixed ordering cost). Examples ofheuristic algorithms include the modified due date scheduling heuristic(which assumes that the objective of the scheduling process is tominimize the total amount of time spent on tasks after their due dates)and shifting bottleneck heuristic (which minimize the time it takes todo work, or specifically, the makespan in a job shop, wherein themakespan is defined as the amount of time, from start to finish, tocomplete a set of multi-machine jobs where machine order is pre-set foreach job, the jobs are assumed to be actually competing for the sameresources (machines) resulting in one or more resources acting as a‘bottleneck’ in the processing, whereby the heuristic, or ‘rule ofthumb’ procedure substantially minimizes the effect of the bottleneck).

A “server” is a computational system (e.g., having both software andsuitable computer hardware) to respond to requests across a computernetwork to provide, or assist in providing, a network service. Serverscan be run on a dedicated computer, which is also often referred to as“the server”, but many networked computers are capable of hostingservers. In many cases, a computer can provide several services and haveseveral servers running. Servers commonly operate within a client-serverarchitecture, in which servers are computer programs running to servethe requests of other programs, namely the clients. The clientstypically connect to the server through the network but may run on thesame computer. In the context of Internet Protocol (IP) networking, aserver is often a program that operates as a socket listener. Analternative model, the peer-to-peer networking module, enables allcomputers to act as either a server or client, as needed. Servers oftenprovide essential services across a network, either to private usersinside a large organization or to public users via the Internet.

“Simulation modeling” refers both to discrete and continuoussimulations. Discrete simulations are also known as discrete eventsimulations, and are event-based dynamic stochastic systems. In otherwords, the system contains a number of states, and is modeled using aset of variables. If the value of a variable changes, this represents anevent, and is reflected in a change in the system's state. As the systemis dynamic, it is constantly changing, and because it is stochastic,there is an element of randomness in the system. Representation ofdiscrete simulations is performed using state equations that contain allthe variables influencing the system. Continuous simulations alsocontain state variables; these however change continuously with time.Continuous simulations are usually modeled using differential equationsthat track the state of the system with reference to time. Thesimulation's output data will only produce a likely estimate ofreal-world events. Methods to increase the accuracy of output datainclude: repeatedly performing simulations and comparing results,dividing events into batches and processing them individually, andchecking that the results of simulations conducted in adjacent timeperiods “connect” to produce a coherent holistic view of the system.Normal analytical techniques make use of extensive mathematical modelswhich require assumptions and restrictions to be placed on the model.This can result in an avoidable inaccuracy in the output data.Simulations avoid placing restrictions on the system and also takerandom processes into account; in fact in some cases simulation is theonly practical modeling technique applicable.

“Transfer Function” (also known as the system function or networkfunction) is a mathematical representation, in terms of spatial ortemporal frequency, of the relation between the input and output of alinear time-invariant system with zero initial conditions and zero-pointequilibrium. Transfer functions are commonly used in the analysis ofsystems such as single-input single-output filters. The term is oftenused to refer to linear, time-invariant systems (LTI). Most real systemshave non-linear input/output characteristics, but many systems, whenoperated within nominal parameters (not “over-driven”) have behaviorthat is close enough to linear that LTI system theory is an acceptablerepresentation of the input/output behavior. While any LTI system can bedescribed by some transfer function or another, there are certainfamilies of special transfer functions that are commonly used. Typicalinfinite impulse response filters are designed to implement one of thesespecial transfer functions. Some common transfer function families andtheir particular characteristics are: Butterfield filter—maximally flatin passband and stopband for the given order; Chebyshev filter (TypeI)—maximally flat in stopband, sharper cutoff than Butterworth of sameorder; Chebyshev filter (Type II)—maximally flat in passband, sharpercutoff than Butterworth of same order; Bessel filter—best pulse responsefor a given order because it has no group delay ripple; Ellipticfilter—sharpest cutoff (narrowest transition between pass band and stopband) for the given order; Optimum “L” filter; Gaussian filter—minimumgroup delay and gives no overshoot to a step function; Hourglass filter;and Raised-cosine filter.

“Transportation theory” refers to the study of optimal transportationand allocation of resources. The transportation problem as it is statedin modern or more technical literature looks somewhat different becauseof the development of Riemannian geometry and measure theory. Examplesof transportation theory functions or principals include Wasserteinmetric, transport function, and the Hungarian algorithm.

The preceding is a simplified summary of the disclosure to provide anunderstanding of some aspects of the disclosure. This summary is neitheran extensive nor exhaustive overview of the disclosure and its variousaspects, embodiments, and/or configurations. It is intended neither toidentify key or critical elements of the disclosure nor to delineate thescope of the disclosure but to present selected concepts of thedisclosure in a simplified form as an introduction to the more detaileddescription presented below. As will be appreciated, other aspects,embodiments, and/or configurations of the disclosure are possibleutilizing, alone or in combination, one or more of the features setforth above or described in detail below.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings are incorporated into and form a part of thespecification to illustrate several examples of the present disclosure.These drawings, together with the description, explain the principles ofthe disclosure. The drawings simply illustrate preferred and alternativeexamples of how the disclosure can be made and used and are not to beconstrued as limiting the disclosure to only the illustrated anddescribed examples. Further features and advantages will become apparentfrom the following, more detailed, description of the various aspects,embodiments, and configurations of the disclosure, as illustrated by thedrawings referenced below.

FIG. 1 is a block diagram of an exemplary three-dimensional supplychain;

FIG. 2 is a block diagram of an exemplary supply chain managementsystem;

FIG. 3 is a block diagram of an exemplary tier 1 control tower;

FIG. 4 is a flow chart of an exemplary data collection module;

FIG. 5 is a flow chart of an exemplary scheduling module;

FIG. 6 is a flow chart of an exemplary analytical engine;

FIG. 7 is a flow chart of an exemplary risk manager;

FIG. 8 is a block diagram of an exemplary supply chain managementsystem;

FIG. 9 is a flow chart of an exemplary security module;

FIG. 10 is a flow chart of an exemplary pricing monitoring module;

FIG. 11 depicts a screenshot according to an embodiment;

FIG. 12 depicts a screenshot according to an embodiment;

FIG. 13 depicts a screenshot according to an embodiment;

FIG. 14 depicts a screenshot according to an embodiment;

FIG. 15 depicts a screenshot according to an embodiment; and

FIG. 16 depicts a screenshot according to an embodiment.

DETAILED DESCRIPTION The Tier 1 Control Tower Supply Chain ManagementSystem

The tier 1 control tower supply chain management system will bediscussed with reference to FIG. 1. Generally, parts and components aremade from materials and/or other parts and components, and products aremade from material, parts, and/or components. Materials are generallyconsidered to be raw materials, or crude or processed materials orsubstances.

A tier 1 control tower 100, in a brand level, typically corresponds to aretail and/or wholesale vendor, supplier, distributor, or other businessthat provides its branded products to end users. These businessestypically invest in research and development, product design, marketing,and brand development. Examples include Apple™, Amazon™, Cisco Systems,Inc.™, and Microsoft Corporation™. The control tower 100 monitors (andcollects information regarding) the product distribution chain, productinventory levels, product demand, and/or prices of competitive productsand, based on the collected information and product demand and priceprojections, dictates to second tier partners, prices, supplyrequirements, and other material terms, and accesses performanceinformation of such second and third tier partners to monitor supplychain performance.

A tier 2 product assembler 104, in an integration level, assembles partsand/or components received from tier 3 part and/or componentmanufacturers into products, which are shipped to the tier 1 vendor,supplier, distributor, or other business for sale. An OEM is an exampleof a Tier 2 product assembler 104. Tier 2 product assembler(s) 104provide, to the tier 1 control tower 100, its respective performanceinformation and performance information received from tier 3 part and/orcomponent manufacturers.

The first, second, . . . nth tier 3 part and/or component manufacturers108 a-n, at the device level, manufacture parts and/or components forassembly by the tier 2 product assembler 104 into products. The first,second, . . . nth tier 3 part and/or component manufacturers 108 a-nprovide, to the tier 2 product assembler 104, its respective performanceinformation and performance information received from tier 4 materialsuppliers.

The first, second, third, . . . mth tier 4 material suppliers 112 a-m,at the raw material level, manufacture and supply to the first, second,. . . nth their 3 part and/or component manufacturers 108 a-n materialsfor use in manufacturing components. The first, second, third, . . . mthtier 4 material suppliers 112 a-m provide, to the tier 3 part and/orcomponent manufacturers, its respective performance information.

Each of the tier 1 control tower 100, tier 2 product assembler 104,first, second, third, . . . nth tier 3 part and/or componentmanufacturer, and first, second, third, . . . mth tier 4 materialsuppliers 112 a-m correspond to an enterprise and/or organization, whichmay or may not be related to or affiliated with another enterpriseand/or organization in the supply chain of FIG. 1.

As shown by the arrows, air, land, and sea logistics providers, such asFedEx, UPS, DHL, other trucking companies, other air freight companies,and other ocean freight carriers, link the various tier partners with anintegrated network of air, sea, and ground capabilities to enableeffective movement of materials, components, and products from sourcesto destinations.

While the above example assumes that performance information is suppliedto the nearest downstream partner (or the party with whom the subjectentity is in privity of contract), it is possible that one or more ofthe tier 2, 3, and 4 partners and/or logistic providers provideperformance information directly to the tier 1 control tower 100. It isfurther to be understood that any number of entities, factories, plants,or other facilities may exist at each of the brand, integration, device,and raw material levels.

“Performance information” typically includes any information relative tosupply chain performance, including, without limitation, one or more ofmanufactured item output projections over a specified time period,production facility sizes and/or locations, raw material,work-in-process, and/or manufactured part, component, and/or productinventory levels, order cycle times, days of supply in inventory,manufacturing resource type, availability, reliability, and/orproductivity (e.g., human and automated resource levels and resultingoutput levels), unit operations (e.g., manufacturing steps, functions,or operations, unloading raw materials, packaging parts, components,and/or products, loading parts, components, and/or products, and thelike), financial factors (e.g., labor rates and costs, energy rates andcosts, raw materials costs, freight costs, tax rates, administrative andoverhead costs, contractual and/or current spot market part, component,and/or product prices (from lower tier components), and the like),number of on time shipments, number of late shipments, order mismatchcount, service quality (e.g., repair returns, repeat repair, no faultfound, etc.), repair cost per unit (e.g., material cost per unit,average repair time, pieces consumed per unit, etc.), inventory value(e.g., spare parts stock, or SWAP stock, inventory turnover, days ofsupply of spare parts, days of supply of SWAP, days sales inventoryspare parts, excess spare parts, excess SWAP stock, return to vendorrate, defective or OHB, and return to vendor or TAT, etc.), historic,current, and/or projected compliance with price, supply requirements,and/or other material terms, historic, current, and/or projected parts,components, and/or product output levels, mean, median and/or average,mode, historic, and/or projected freight transportation times, delays,or requirements, and the like. The performance information can beassociated with a date, month, and/or season-of-year. Metrics can begenerated from the performance information, such as on time shipmentrate or percentage, late shipment rate or percentage, product rejectionrate based on nonconformance with one or more restrictions,specifications, and/or requirements, parts, components, and/or productacceptance rate based on conformance with one or more restrictions,specifications, and/or requirements, and the like.

FIG. 2 depicts a communications networked architecture 200 according toan embodiment.

The tier 1 control tower 100 comprises a tier 1 control tower server 204and associated database management system (not shown) and database 208.

The tier 1 control tower server 204 can be any computerized process thatshares a resource with one or more client processes. It may run one ormore services (typically as a host), to service the needs of othercomputers on the network. Typically, the tier 1 control tower server 204is a computer program running to serve the requests of other programs.

The database 208 can be any organized collection of data and theirsupporting data structures. The database can be based on any data model,including the relational model, entity-relationship model, object model,object relational model, XML, or other database model. The database 204can include, for each enterprise and/or organization in the supplychain, not only performance information but also transactional documents(e.g., purchase order, material safety data sheets, bill of materials,supply and/or manufacturing agreements, or RMAs, and the like), name,geographical location, geopolitical location, part and/or componentand/or product and/or material type and/or identity supplied by theenterprise and/or organization, current spot market and/or contractualsales price of the part and/or component and/or product and/or materialtype supplied by the enterprise and/or organization, respectiveperformance metrics of the enterprise and/or organization, part and/orcomponent and/or product and/or material supply and/or purchasecommitment with another enterprise and/or organization in the supplychain, specifications and requirements for part(s) and/or component(s)and/or product(s) and/or material(s) supplied and/or purchased by theenterprise and/or organization, part and/or component and/or productand/or material quantity and shipment dates and expected arrival datesat the next enterprise and/or organization in the supply chain, ordercycle and/or turnaround times, shipment and/or order volume, totalnumber of shipments, number of on time shipments, number of lateshipments, order mismatch count, repair details, and each enterpriseand/or organization is associated with one or more other enterpriseand/or organizations in the supply chain to indicate a contractual orother supply relationship. Each enterprise and/or organization isnormally assigned a role identifier, such as buyer, seller, supplier,manufacturer, material supplier, and the like, to describe the nature ofthe relationship of the enterprise and/or organization to each of theassociated enterprise(s) and/or organization(s) in the supply chain.

The tier 2 assembler has a corresponding server 212 to provideperformance and other information, directly or indirectly, to the tier 1control tower server 204.

Each of the first, second, . . . nh tier 3 part/component manufacturershas a corresponding server 216 a-n to provide performance and otherinformation, directly or indirectly, to the tier 1 control tower server204.

Each of the first, second, third, . . . mth tier 4 material suppliershas a corresponding server 220 a-m to provide performance and otherinformation, directly or indirectly, to the tier 1 control tower server204.

The shipment enterprise and/or organization server 250 represents thefreight enterprises or organizations handling shipments between nodes ofthe supply chain. The freight enterprises and organizations can be anyentity providing shipping services. Exemplary freight enterprises andorganizations include railway companies, short and long haul truckingcompanies, freight company servers (to provide freight trackinginformation, freight movement projections between two locations, and thelike), shipping lines, maritime shipping companies, container shippingcompanies, Ro-ro shipping companies, transoceanic shipping companies,logistics services or courier companies, and the like. The shipmententerprise and/or organization server 250 can provide to the tier 1control tower server 204 provide freight tracking information, freightmovement projections between two locations, and the like.

The accessible information source(s) 224 include any source ofinformation relevant to supply chain performance, including, withoutlimitation, news sources and/or aggregators (to provide news on currentevents that may impact positively or negatively the supply chainperformance, such as political coup d'etates, changes or upheavals,environmental conditions and events (e.g., storms, floods, earthquakes,tsunamis, typhoons, volcanic eruptions, forest fires, and other naturaldisasters, and the like), criminal acts (e.g., piracy, hijacking, theft,arson, vandalism, and the like), acts of violence (e.g., terrorism, war,political upheaval, military action, and the like), news reports on andannouncements by a partner or competitor, scheduled events or holidays(e.g., religious, political, or other holidays), freight disruptions(e.g., train derailment, oceangoing vessel sinking, airplane crash,freight embargos, naval blockades, and the like), energy shortages,disruptions, or blackouts, and labor disruptions (e.g., strikes orthreatened strikes)), weather data sources (e.g., the National WeatherService, national and local news sources, the Weather Channel™, WeatherSource™, worldweatheronline.com, and the like), governmental entities(such as courts, law enforcement authorities, geological surveys,disaster relief agencies, and the like to provide legal or regulatorychanges or requirements, lawsuits, bankruptcy filings, and the like, andother information), law enforcement or military authorities (e.g., toprovide information on criminal acts (e.g., piracy, hijacking, theft,arson, vandalism, and the like), and acts of violence (e.g., terrorism,war, revolution, political upheaval, military action, and the like).Such information sources can be monitored using word cloud techniques,which graphically represent word usage frequency. Generally, the morefrequent a word or group of words is used the greater the likelihoodthat the fact or event described by the words or group of words exists.The words or group of words can further be weighted for reliability bythe source, with law enforcement and military authorities being given ahigher or more reliable weighting than news sources.

The various servers and sources are connected by a circuit and/or packetswitched wide area network (“WAN”) that covers a broad area (e.g., anytelecommunications network that links across metropolitan, regional, ornational boundaries) using private and/or public network transports. Anexemplary WAN is the Internet.

FIG. 3 depicts an example of a supply chain monitoring system 302maintained by the tier 1 control tower 100. As will be appreciated, thesupply chain monitoring system can be maintained by any one of the tier1, 2, 3, and/or 4 entities or an entity independent of the foregoing.The supply chain monitoring system 302 includes a data collection module300, a scheduling module 304, a historical state module 308, ananalytical engine 312, a risk manager 316, and a reporting module 320,connected by a local area network or bus 324.

The data collection module 300 collects performance information fromtier 2, 3, and/or 4 entities and freight companies in the supply chainand from accessible information source(s) 224. It further collectsinformation regarding product inventory levels currently on hand at thetier 1 control tower. The data collection module 300 can parse thecollected information, extract relevant information items, andoptionally tag the extracted information items with an information typetag. The data collection module 300 can include a database managementfunction that stores, updates and otherwise manages the data in thedatabase 208 in accordance with a selected data model. The datastructures are typically associated with one or more enterprises and/ororganizations in the supply chain. Transactional documents, such aspurchase orders, material safety data sheets, and bills of material,contain references to all owners down the organization level, havecorresponding role types and functions specified (e.g., only a buyerRolecan change requestQuantity field), and include preferences and settingsreferenced to an appropriate level (e.g., enterprise, organization (orthe part of the enterprise involved in the supply chain transaction),user, etc.).

Events stored in the database 208 typically include event category,event type, event subtype and event severity tags. Event categoriesinclude, for example, natural disaster (e.g., natural disaster event andwherein the natural disaster is one or more of an earthquake, tsunami,volcanic eruption, fire, flood, avalanche, and landslide), weather(e.g., storm, typhoon, hurricane, cyclone, tornado, wind, and blizzard),political (e.g., coup d'etat, sabotage, terrorism, act of war, militaryaction, police action, embargo, and blockade), and business (e.g., amaritime vessel sinking, train derailment, freight vehicle wreck, deviceor system malfunction, criminal activity, airplane crash, labordisruption, lawsuit, financial insolvency, and bankruptcy). Event typesinclude, for example, geologic event, atmospheric event, geo-political,labor, and insolvency. Event subtypes include, for geologic, earthquake,volcanic eruption, tsunami, flood, and landslide; for atmospheric,storm, hurricane, cyclone, tornado, wind, and blizzard; forgeo-political coup d'etates, sabotage, terrorism, and piracy; for labor,strike; and for insolvency, bankruptcy. The severity tag can include oneor more of emergency, advisory, watch, and warning. Other tags will beobvious to those of ordinary skill in the art based on the teachings ofthis disclosure. A start and end time can be associated with thetemporal impact of the event on the supply chain.

The collected information generally falls into two categories, namelystatic supply chain information (information items that generally do notchange or change infrequently such as sites, enterprise and/ororganization names, and the like) and dynamic supply chain data(information items that change frequently such as purchase orders,forecasts, and the like).

The scheduling module 304 provides scheduling information, includingprojected shipment arrival dates for products from the tier 2 productassembler 104 and required shipment departure dates for branded productsto customers, wholesalers, and/or retailers. Each of the shipmentarrival and departure dates can be linked to a set of data structuresdescribing the shipment, including shipment source and destination,freight carrier, freight tracking information, current shipment status,shipment contents (by product type and number), date of shipment, andthe like). The projected shipment arrival dates can be received from thetier 2 product assembler 104 and/or freight carrier. The shipmentdeparture dates are determined by the tier 1 control tower based oncontractual requirements, retailer and/or wholesaler current orprojected inventory levels, retainer and/or wholesaler order, and thelike.

The historical state module 308 tracks past performance for each entityand/or entity facility in the tier 2-4 and freight carriers (e.g.,compares the actual product shipment arrival date against a selecteddate (received from the entity, required by contract or order, and/orprojected by the tier 1 control tower 100)) and distribution chaindemands (to identity seasonal trends). The past performance for anentity can be used to determine and assign a level of confidence inproduct deliveries from the entity being received by a selected date(received from the entity, required by contract or order, and/orprojected by the tier 1 control tower 100). The level of confidence,when low, may provide a basis to order additional product from a morereliable source. The level of confidence can be based on pastperformance of each supplier or each different facility of a commonsupplier.

The analytical engine 312 receives performance and other data from thedata collection module 300, scheduling information from the schedulingmodule 304, and historical information (such as a level of confidence)from the historical state module 308 and, based on the information,forecasts incoming shipment arrival times and outgoing shipmentdeparture times and identifies any inability to meet distribution chainrequirements, commitments or objectives (e.g., orders, contractualcommitments, policies, objectives, etc.) (a “noncompliant event”). Thisinformation is provided, by the analytical engine 312 to the riskmanager 316. The analytical engine 312 can be a type of situationalawareness application that looks at aspects of the current state of thesupply chain as well as the structural relationships and considers theeffect of both internal and external events on the supply chain. Bothpast events and forecasted events can be considered by the analyticalengine 312. The application can determine not only what happened to thesupply chain but also what may happen to the supply chain, therebyproviding not only a reactive but also proactive model for problemresolution.

In one application, the analytical engine 312 relies primarily onreported performance information received from tier 2 assembler(s) 212,tier 3 component manufacturer(s), tier 4 raw material supplier(s) and/orfreight carrier(s) in estimating compliance with product distributionchain requirements. Disruptive events received from an accessibleinformation source 224 are used as the basis of a query to thepotentially impacted tier 2 assembler(s) 212, tier 3 part/componentmanufacturer(s), tier 4 material supplier(s) and/or freight carrier(s)for updated performance information. The query may be generatedautomatically or manually by tier 1 management.

In one application, the analytical engine 312 determines, based onperformance information received from the historical state module 308, aperformance rating for each enterprise and/or organization in the supplychain. The performance rating can be based on a scale from lowestperformance level to highest performance level.

In one application, the analytical engine 312 relies not only onreported performance information but also internally generatedprojections in estimating compliance with distribution chainrequirements. The compliance determination is based one or morecomparisons, including a comparison of the material and/or part and/orcomponent and/or product shipment delivery date based on the reportedperformance information against the material and/or part and/orcomponent and/or product distribution chain shipment requirement(s) (asin the prior paragraph), a comparison of the material and/or part and/orcomponent and/or product shipment delivery date based on the reportedperformance information against the internally generated projectedmaterial and/or part and/or component and/or product shipment deliverydate, and a comparison of the material and/or part and/or componentand/or product shipment delivery date based on the reported performanceinformation against the internally generated projected material and/orpart and/or component and/or product shipment delivery date.

The estimated or projected delivery date for an order can include anassociated probability or likelihood and, optionally, an associatedrange of arrival dates that the items in the order will be timelyreceived by the selected arrival date or within the range of arrivaldates. The range of arrival dates can be selected using a standarddeviation of arrival times based on current and/or historic performanceinformation and/or other relevant information. For example, a historicreliability or probability of timely receipt at a destination facilityfrom the selected lower tier facility, and optionally associatedstandard deviation of historic receipt dates relative to a target date,can be used to provide the probability and optionally standard deviationof the destination facility receiving a current shipment from theselected lower tier facility. The probability and/or standard deviationcan be used by the risk manager to determine whether or not to orderadditional material and/or part and/or component and/or product from analternate facility. This determination can use a probability threshold,for instance, that would require or recommend order placement to analternative facility if the probability of the order timely arriving istoo low or no order placement to the alternative facility if theprobability of the order timely arriving is acceptable (e.g., exceedsthe probability threshold).

For any facility in a tier, the probability could be the sum or othermathematical combination of probabilities for each upstream facility inlower tiers in a direct or indirect supply relationship with a selectedfacility. For example, if a third part/component manufacturing facilityin tier 3 has a 50% probability of receiving timely raw material from afourth and/or alternative facility in tier 4, a second productmanufacturing facility or assembler in tier 2 has a 50% probability ofreceiving timely a necessary product part and/or component from thethird facility and/or an alternative tier 3 facility, and the firstfacility in tier 1 has a 25% probability of receiving the producttimely. When a selected facility, such as a product assembler, has a 50%probability of receiving timely a first necessary component from a firsttier 3 part/component manufacturer and a 25% probability of receivingtimely a second necessary component from a second tier 3 part/componentmanufacturer, the probability of a third tier 1 facility receiving theproduct timely from the selected product manufacturing or assemblingfacility is the lower of the two or 25%.

A number of algorithms may be used in generating the internal estimates.

One algorithm uses a critical path method (“CPM”), or an algorithm forscheduling a set of project activities. CPM constructs a model, at eachsupply chain facility and/or manufacturer, supplier, and/or assemblerand/or for the overall supply chain, that includes one or more of thefollowing: (a) a list of all activities required to deliver the productshipment to the tier 1 control tower, (b) the time (duration) that eachactivity or operation in the supply chain will take to completion, and(c) the dependencies between the activities. Using these values, CPMcalculates the longest path of planned activities to the end of theproduct delivery cycle, and the earliest and latest that each activitycan start and finish without making the product delivery cycle longer.This process determines which activities are “critical” (i.e., on thelongest path) and which have “total float” (i.e., can be delayed withoutmaking the product delivery cycle longer). In project management, acritical path is the sequence of supply chain network activities whichadd up to the longest overall duration. This determines the shortesttime possible to complete the product delivery cycle. Any delay of anactivity on the critical path directly impacts the planned productdelivery cycle completion date (i.e. there is no float on the criticalpath). A product delivery cycle can have several, parallel, nearcritical paths. An additional parallel path through the network with thetotal durations shorter than the critical path is called a sub-criticalor non-critical path.

One algorithm uses queueing theory by characterizing the supply chain asone or more queues of work pieces being “serviced” at each tier andthereby defining supply chain behavior based on queue behavior. As willbe appreciated, queueing theory is generally considered a branch ofoperations research because the results are often used when makingbusiness decisions about the resources needed to provide service. Thequeueing model can be based on a Poisson process and its companionexponential probability distribution. A Poisson process models random orpseudo-random events (such as a work piece arrival from a lower tierpartner, a supply chain disruptive event, or the completion of an actionrequested of a resource over which the servicing tier has no control) asemanating from a memoryless process. That is, the length of the timeinterval from the current time to the occurrence of the next event doesnot depend upon the time of occurrence of the last event. In the Poissonprobability distribution, the observer records the number of events thatoccur in a time interval of fixed length. In the (negative) exponentialprobability distribution, the observer records the length of the timeinterval between consecutive events. In both, the underlying physicalprocess is memoryless. Examples of queueing theory functions orprincipals include BCMP network, Buzen's algorithm, Ehrenfest model,fork join queue, Gordon-Newell network, Jackson network, Little's law,Markovian arrival processes, Pollaczek-Khinchine formula,quasireversibility, random early detection, renewal theory, the Poissonprocess, and the like. Models based on the Poisson process often respondto inputs from the environment in a manner that mimics the response ofthe system being modeled to those same inputs. The analyticallytractable models that result yield both information about the systembeing modeled and the form of their solution. Even a queueing modelbased on the Poisson process that does a relatively poor job ofmimicking detailed system performance can be useful. The fact that suchmodels often give “worst-case” scenario product cycle evaluations cansupport the risk manager including a safety factor in supply chainchanges and modifications, including product delivery requirements.Queueing models are frequently modeled as Poisson processes through theuse of an exponential distribution.

One algorithm is a scheduling algorithm, which considers productproduction scheduling and shipping and includes forward and/or backwardscheduling. Forward scheduling is planning the tasks from the dateresources become available to determine the shipping date or the duedate. Backward scheduling is planning the tasks from the due date orrequired-by date to determine the start date and/or any changes incapacity required. Stochastic scheduling algorithms can include economiclot scheduling problem (which is concerned with scheduling theproduction of several products on a single machine in order to minimizesubstantially the total costs incurred (which include setup costs andinventory holding costs) and the economic production quantity model(which determines the quantity a enterprise and/or organization and/orretailer should order to minimize the total inventory costs by balancingthe inventory holding cost and average fixed ordering cost). Examples ofheuristic algorithms include the modified due date scheduling heuristic(which assumes that the objective of the scheduling process is tominimize substantially the total amount of time spent on tasks aftertheir due dates) and shifting bottleneck heuristic (which minimize thetime it takes to do work, or specifically, the makespan in a job shop,wherein the makespan is defined as the amount of time, from start tofinish, to complete a set of multi-machine jobs where machine order ispre-set for each job, the jobs are assumed to be actually competing forthe same resources (machines) resulting in one or more resources actingas a ‘bottleneck’ in the processing, whereby the heuristic, or ‘rule ofthumb’ procedure substantially minimizes the effect of the bottleneck).

One algorithm is simulation modeling using discrete or continuoussimulations. Discrete simulations are also known as discrete eventsimulations, and are event-based dynamic stochastic systems. In otherwords, the system, or supply chain, contains a number of states, and ismodeled using a set of variables. If the value of a variable changes,this represents an event, and is reflected in a change in the system'sstate. As the system is dynamic, it is constantly changing, and becauseit is stochastic, there is an element of randomness in the system.Representation of discrete simulations is performed using stateequations that contain all the variables influencing the system orsupply chain. Continuous simulations also contain state variables; thesehowever change continuously with time. Continuous simulations areusually modeled using differential equations that track the state of thesystem, or supply chain, with reference to time. The simulation's outputdata will only produce a likely estimate of real-world events (i.e.,product shipment delivery). Methods to increase the accuracy of outputdata include: repeatedly performing simulations and comparing results,dividing events into batches and processing them individually, andchecking that the results of simulations conducted in adjacent timeperiods “connect” to produce a coherent holistic view of the system.Normal analytical techniques make use of extensive mathematical modelswhich require assumptions and restrictions to be placed on the model.This can result in an avoidable inaccuracy in the output data.Simulations avoid placing restrictions on the system and also takerandom processes into account; in fact in some cases simulation is theonly practical modeling technique applicable.

The analytical engine 312 can use pattern or template matching todetermine internal estimates. The patterns or templates can be based onhistorical data patterns and observed shipment times and/or on patternsor templates predetermined or predefined by system administrators. Theanalytical engine 312 can search by one or more of the time, locationand setting. For example, for an earthquake in Asia having a specifiedseverity level, the analytical engine 312 can search for otherearthquake events in Asia over the last three years having a similarseverity level and determine the actual shipment times and/oradministrator shipping estimates or projections made for the currentlyselected or other supply chain to determine a current estimate orprojection.

The analytical engine 312 can detect unreported events by identifyingunexpected varations in collected performance information. For example,where one or more selected nodes of the supply chain experience a suddendrop in rate of on-time shipments or rise in rate of late shipments andthe drop is sustained over a selected period, the analytical engine 312can deduce that a disruptive event has occurred. The possibility of anoccurrence of an unreported disruptive event can be reported to a systemor supply chain enterprise and/or organization administrator. Likewise,the severity of an event and/or shipment projections can be changed andrendered more accurate by observing actual behavior following creationof the event or estimate or projection. This information can also beused to refine temporally proximate estimates or projections.

The analytical engine 312 and risk manager 316 can use other variablesand/or algorithms to determine the relative health of the supply chain.For example, the analytical engine 312 can employ a metric—CpX, whichcan be a measure of risk and capable of substantially optimizing thesupply chain. The metric can be determined through the collection,aggregation, and transformation of supply chain data, includingperformance information, and, when optimized, can modify systemparameters of the logistic or supply chain system to reduce and/oroptimize risk profiles for any selected supply chain parameter orobject, typically a given product, a selected product line, and/or acustomer account.

Risk can be determined given a time series of data collected by the datacollection module. This data can be presented either as a first lineararray (1×N) where N is the number of factors collected. The factors caninclude one or more of the factors, parameters, or supply chaincharacteristics identified herein. The factors can include risk factors,such as economic risk, environmental risk, geopolitical risk, societalrisk, and technological risk. A transfer function (N×M) can relate thecollection of such (risk) factors to variability (risk) of criticalfactors, (be they cost, time to delivery, the same or another riskfactor, etc.), which is the (1×M) linear array. The (1×N) linear arraycan also be transformed into a single number or factor or given acoloration indicative of an “overall” metric of risk (variability). Theoverall metric of risk can be a supply chain health index or risk.

After optimization of the collected factors and comparing real data, thetransfer function (N×M) can be substantially optimized—and it canrepresent the operational parameters of the supply chain (for better orworse).

To optimize the supply chain (or substantially minimize the magnitude ofthe 1×M scalar), one can apply a reverse transform function and finetune the factors in the (1×N) linear array to effect the change—meaningfor each optimal element 1 to . . . N, actual operations (e.g., ordercycle, warehouse sizing, assembly line capacity, order aggregation,price, etc.) will be changed or modified to achieve the desired riskprofile. Alternatively, risk protection can be set, configured, ordetermined at various levels by setting the scalar (high, medium, low)and changing the various offerings to meet the customer need—as somecustomers can deal with risk better than others).

Alternatively, given a multiple set of (1×N) and (1×M), a multitude orplurality of transfer functions can be determined, particularly wherestate or situational differences exist among one or more of businesssegments, product portfolios, customers profiles, etc. In such cases,the 1×M (minimum) linear array would likely be different, as would thesubstantially optimal 1×N linear array.

In cases where each supply chain situation or state is mutuallyexclusive, the solutions themselves will be likewise, mutuallyexclusive. In new scenarios, the linear combination of such solutionwould be applicable in direct proportion to their contribution, providedthat there is no correlation between the solutions.

The risk manager 316 applies a rule or policy set or template to theinformation or output received from the analytical engine 312 andprovides reporting information to the reporting module 320 forpresentation to a (human) manager. The reporting information may includenot only a warning (with an associated probability and/or level ofconfidence) that a noncompliant event will occur and optionally arecommendation on how to mitigate and/or avoid the noncompliant event.Mitigation recommendations include, for example, ordering products froma different facility of the tier 2 product assembler 104 and/or from adifferent tier 2 product assembler 104, using a type of freight companyor specific freight company to provide faster incoming and/or outgoingproduct shipment, cancelling or altering an existing order (e.g.,increase or decrease product quantity and/or delay or expedite productshipment date) with a tier 2 product assembler 104 and/or downstreamdistribution chain entity, shipping product from a different tier 1facility to the selected destination in the distribution chain to offsetthe noncompliant event, and ship a different product to the selecteddestination in the distribution chain to offset the noncompliant event.The recommendation can be performed automatically by the risk manager316.

The risk manager 316 can identify problems or choke points orbottlenecks in the supply chain, generate alerts and/or notifications toadministrators of predetermined events (such as a monitored parameterfalling below or exceeding a selected threshold), and/or providerecommended changes to the supply chain to provide greater reliability,more reliable and faster material and/or part and/or component and/orproduct manufacture and delivery cycles, more material turns, andreduced waste. The risk manager 316 at the tier 1 control tower 100 cando this, for example, by analyzing the reported performance informationusing advanced planning and scheduling techniques by which raw materialsand production capacity are optimally allocated to meet demand.Recommendations could include restructuring tier 1, 2, 3 and 4relationships, using differently located facilities for lesser orgreater production, using different freight modes and/or carriers, andreconfiguring the layout and/or production unit operations within aselected facility. A performance risk can be associated with eachrecommendation based on factors, such as performance rating, geographiclocation of the recommended enterprise and/or organization relative tothe geographic locations of the upstream enterprise and/or organization(if any) supplying the recommended enterprise and/or organization and ofthe downstream enterprise and/or organization (if any) receivingmaterial and/or product from the recommended enterprise and/ororganization, and/or the likelihood of a disruptive event impacting therecommended enterprise and/or organization and/or a shipment lineassociated therewith.

The risk manager 316 can determine a possible or potential financialimpact on the enterprise or organization associated with eachrecommendation or, in the absence of any action, simply as a result ofthe event. The possible or potential financial impact can be done on oneor more affected product lines and/or for the enterprise or organizationas a whole. A risk or probability can be assigned to each possible orpotential financial impact to form a type of risk portfolio. Pricinginput from a price monitoring module (discussed below) can assist indetermining product price increases as a result of the event. Decreasesin demand for the product can be projected based on the price increase.The decreased demand can then be converted into a projected gross salesrevenue to be used in the financial forecast. The possible or potentialfinancial impact can be determined for an instance of an event orproactively if a selected event were to occur. Electronic manufacturingservices, in particular, would benefit from this type of financialimpact analysis.

The risk manager 316 can apply manufacturing process management or MPMand/or enterprise resource planning (“ERP”) and/or materials requirementplanning (“MRP”) techniques. MPM is a collection of technologies andmethods used to define how products are to be manufactured. MPM differsfrom ERP/MRP, which is used to plan the ordering of materials and otherresources, set manufacturing schedules, and compile cost data. MPM canprovide the central repository for the integration of all these toolsand activities and aid in the exploration of alternative production lineor sequence or cycle scenarios; making assembly lines more efficientwith the aim of reduced lead time to product launch, shorter producttimes and reduced work in progress (WIP) inventories as well as allowingrapid response to product or product changes.

The risk manager can use scheduling algorithms to determine and/oridentify recommended changes to the supply chain.

The risk manager can use pattern or template matching to determineand/or identify recommended changes to the supply chain. The patterns ortemplates can be based on historical data patterns and observedadministrator responses and/or on patterns or templates predetermined orpredefined by system administrators. The risk manager can search by oneor more of the time, location and setting. For example, for anearthquake in Asia having a specified severity level, the risk managercan search for other earthquake events in Asia within the last threeyears having a similar severity level and determine the changes to thecurrently selected or other supply chain to determine a currentlyrecommended set of changes.

The risk manager can use simulation modeling to determine and/oridentify recommended changes to the supply chain.

The risk manager can use transportation theory to determine the optimaltransportation and/or allocation of supply chain resources. Examples oftransportation theory functions or principals include Wassertein metric,transport function, and the Hungarian algorithm.

The risk manager can use capacity planning, which is the process ofdetermining the production capacity needed by the supply chain to meetchanging demands for the branded products. In the context of capacityplanning, “design capacity” is the maximum amount of work that thesupply chain is capable of completing in a given period, “effectivecapacity” is the maximum amount of work that the supply chain is capableof completing in a given period due to constraints such as qualityproblems, delays, material handling, etc.

The risk manager can intelligently relate the geographical location ofeach facility in each tier with a partner facility in a higher tierand/or the relative shipping costs and/or standard deviation thereoffrom a facility in one tier to a partner facility in a higher tier andcontrol relationships to reduce or substantially minimize transportationcosts. This mapping, which can be in the form of a unit shipping costfrom each facility in a lower tier to each facility in the adjacenthigher tier, can also be used to intelligently order materials and/orcomponents and/or products from a lower tier facility to an upper tierfacility experiencing a supply constraint so as to maintain lowertransportation or shipping costs.

The risk manager can intelligently relate the geographical location ofeach facility in each tier with a partner facility in a higher tierand/or the relative shipping time and/or standard deviation thereof froma facility in one tier to a partner facility in a higher tier andcontrol relationships to reduce or substantially minimize transportationtime. This mapping, which can be in the form of a shipping time from apoint of loading at each facility in a lower tier to arrival at eachfacility in the adjacent higher tier, can also be used to intelligentlyorder materials and/or components and/or products from a lower tierfacility to an upper tier facility experiencing a supply constraint soas to maintain lower transportation or shipping times to substantiallyminimize disruptions in the distribution chain.

The risk manager can intelligently relate the rate of turnover or unitmanufacturing time and standard deviation thereof from time of receiptof an order for a manufactured item to the time of shipping of themanufactured item for each facility in each tier, optionally associatedwith a shipping time required to ship the manufactured item to a partnerfacility in a higher tier and/or standard deviation thereof and controlrelationships to reduce or substantially minimize unit productmanufacturing time. This mapping can also be used to intelligently ordermaterials and/or components and/or products from a lower tier facilityto an upper tier facility experiencing a supply constraint so as tomaintain lower product manufacturing and transportation or shippingtimes to substantially minimize disruptions in the distribution chain.

The risk manager can intelligently relate the unit manufacturing cost,or price, of material and/or component and/or product and/or standarddeviation thereof from each facility in each tier and optionally unitshipping costs from the facility in a lower tier to a partner facilityin a higher tier and/or standard deviation thereof, and control supplyand facility relationships to reduce or substantially minimize unitcosts and/or prices at the lower tier facility or as delivered at thedestination partner facility in the adjacent higher tier. This mapping,which can be in the form of a unit cost or price, optionally unitshipping cost from each facility in a lower tier to each facility in theadjacent higher tier, and total unit cost or price as delivered, can beused to intelligently order materials and/or components and/or productsfrom a lower tier facility to an adjacent upper tier facility so as tomaintain lower transportation or shipping costs.

In either of the prior cost mappings, each facility can have, in theadjacent lower tier and adjacent higher tier, order of partner facilitypreferences in the event of a need to order additional material and/orcomponent and/or product to an upper tier facility experiencing a supplyconstraint so as to maintain lower unit costs and/or prices at thesource facility and/or unit transportation or shipping costs and/ortotal unit costs and/or prices as delivered. In this manner, when adisruptive event adversely impacts supply from a facility or a facilityis otherwise unable to meet an existing or new order for material and/orcomponent and/or product the risk manager can easily select a nextpreferred supplier and forward the order or unsatisfied portion of theorder to the next preferred facility.

As will be appreciated, any of the other estimates or projectionsdescribed herein can include a level of confidence or probability thatthe estimate or projection is true or false (as appropriate).

The reporting module 320 provides the reporting information to tier 1management. The reporting module 320 can not only provide reportscontaining performance information but also generate map displays. FIGS.11-17 are a series of screen shots demonstrating reporting informationprovided by the reporting module 320.

With reference to FIG. 16, the display 1700 shows locations of varioussupply chain nodes, including the tier 2 product assembler 104, first,second, . . . nth tier 3 part/component manufacturers 108 a-n, andfirst, second, third, . . . mth tier 4 material suppliers 112 a-m.Material and/or part and/or component and/or product shipment lines 1704a-g between the various related nodes can be shown. Different colors orshades of a common color can be assigned to each shipment line toindicate on-time shipments, slightly delayed shipments, moderatelydelayed shipments, and heavily delayed shipments. A disruptive event,such as a weather event, earthquake event, business disruption event,geo-political event, and financial disruption event, can be shown on themap at a location 1708 impacted by the event. A range of disruption 1712is also assigned to the event indicating a likely spatial range impactedby the event. As will be appreciated, different event types and eventsfor a given event type can have differing assigned spatial ranges ofdisruption. For example, an earthquake may have a larger spatial rangeof disruption than a storm, and an 8.0 earthquake on the Richter scalewould have a larger spatial range of disruption than a 5.5 earthquake onthe Richter scale. A range can be modeled by many techniques, such as byusing a shape file. Additionally, moving a cursor over a node, shipmentline, or event can cause a box or icon, such as shown by boxes 1722 and1726, to appear providing relevant information about the associated oneof the node, shipment line, or event. For example, relevant informationabout the node can include enterprise and/or organization name,materials and/or part and/or component and/or products supplied by theenterprise and/or organization, and one-hop related enterprises and/ororganizations (e.g., the supplier to the selected node and the purchaserfrom the selected node). Relevant information about the shipment linecan include the name of the freight carrier, number, type, and value ofmaterial and/or part and/or component and/or product currently beingshipped, and the current status of the shipment. Relevant informationfor the event can include the event category, type and subtype andseverity, number of materials and/or part and/or component and/orproducts impacted, number of downstream parts and/or components and/orproducts impacted (such as the parts and/or products supplied to thetier 2 product assembler 104), potential financial impact on the tier 1control tower 100, and number of supply chain sites affected. The boxesin FIG. 16 show relevant shipment information including a number andvalue of products, parts, and/or components currently en route along thecorresponding shipment line.

With reference to FIG. 11, the reporting module provides a display 1100showing a location 1104 and impacted range 1108 of an event (a 4.9earthquake) and locations 1112 and descriptions 1116 of variousenterprises and/or organizations in the supply chain, namely companies1-4 with relevant information provided about each enterprise and/ororganization (e.g., role, location, and products, parts, and/orcomponents provided to the supply chain). By moving the cursor over thelocation of the event, a box 1120 appears providing event information,including a description and location of the event, number of productsimpacted by the event, number of parts impacted by the event, potentialfinancial impact of the event, and supply chain sites affected by theevent. A message 1124 is also provided at the upper part of the display1100 indicating a number of events (e.g., 4) potentially impacting thesupply chain at the present time.

With reference to FIG. 12, the reporting module provides a display 1200showing an administrator input box 1204 to provide event information tothe data collection module. The input box 1204 includes fields for eventtype 1208, event subtype 1212, event epicenter 1216 (which lets theadministrator elect whether to have the data collection module locatethe epicenter or provide latitude and longitude of the epicenter),country of epicenter location 1220, postal code of epicenter location1224, radius impacted by the event 1226, current risk (or severity)level 1228, event expiration date and time 1232, and event description1236.

With reference to FIG. 13, the reporting module provides a display 1300providing information about the impact of a selected event on the supplychain. The display 1300 includes a picture 1304 showing the epicenterand impact radius of the event and supply chain sites affected withinthe impact radius, a description of the event 1308, products potentiallyaffected by the event 1312, parts and/or components potentially affectedby the event 1316, and other potential supply chain impacts 1320.

With reference to FIG. 14, the reporting module provides a display 1400showing events occurring over a selected time period. Each eventdescription 1404 shows event type, event date, event severity, number ofproducts, parts, or components affected, and revenue impact on theselected enterprise and/or organization.

With reference to FIG. 15, the reporting module provides a display 1500showing a product, part, or component supplier description for aselected company (e.g., enterprise or organization). The descriptionincludes a supplier risk category 1504 (e.g., low, moderate, and high)and the various factors used in developing the risk category. Thesefactors are: supplier performance score 1508 (based on historicalsupplier performance information), supplier location score 1512 (thedegree to which the supplier site location can positively or negativelyimpact supply chain performance), supplier financial score 1516 (thedegree to which the supplier financial condition can positively ornegatively impact supply chain performance), and supplier geo-politicalscore 1520 (the degree to which the geo-political location of thesupplier can positively or negatively impact supply chain performance).The risk category is determined by the risk manager for each tier 1control tower server 204, tier 2 assembler server 212, first, second, .. . nth tier 3 component manufacturer server 216 a-n, and first, second,third, . . . mth tier 4 material (e.g., part and/or component) supplierserver 220 a-m, and the performance, location, financial, andgeo-political scores are determined by the analytical engine, for eachtier 1 control tower server 204, tier 2 assembler server 212, first,second, . . . nth tier 3 component manufacturer server 216 a-n, andfirst, second, third, . . . mth tier 4 material supplier server 220 a-m.The performance, location, financial, and geo-political scores can beassigned by the analytical engine and/or administrators. The supplierrisk category and performance, location, financial, and geo-politicalscores are not limited to suppliers but may be assigned not only to thetier 1 control tower 100, tier 2 assembler 104, first, second, . . . nthtier 3 component manufacturer 108 a-n, and first, second, third, . . .mth tier 4 material supplier 112 a-m but also freight carriers betweenand among two or more of the foregoing.

Operation of the Tier 1 Control Tower Supply Chain Management System

Referring to FIG. 4, the operation of the data collection module 300will be discussed.

In step 400, the data collection module 300 receives a stimulus. Stimuliinclude, for example, a request from a tier 1 manager, reportedperformance information received from a lower tier partner, a requestfrom the risk manager 316 and/or scheduling module 304 and/or analyticalengine 312, passage of time, and the like.

In step 404, the data collection module 300 selects a (next) supplychain node to query for performance information.

In step 408, the data collection module 300 accesses, or receives, theperformance information.

In decision diamond 412, the data collection module 300 determineswhether there is a next supply chain node to be considered forperformance information. If so, the data collection module 300 returnsto step 404. If not, the data collection module 300 returns to step 400and awaits the next stimulus instance.

Referring to FIG. 5, the operation of the scheduling module 304 will bediscussed. In step 500, the scheduling module 304 receives a stimulus.Stimuli include, for example, a request from a tier 1 manager,notification by the data collection module 300 of newly received and/orupdated reported performance information, a request from the riskmanager 316 and/or analytical engine 312, passage of time, and the like.

In step 504, the scheduling module 304 updates supply chainnode-supplied scheduling information, or product delivery estimates,based on the reported performance information and/or the internallygenerated product delivery estimates. The scheduling informationincludes, for example, projected shipment arrival dates for productsfrom the tier 2 product assembler 104 and required shipment departuredates for branded products to customers, wholesalers, and/or retailers.Each of the shipment arrival and departure dates can be linked to a setof data structures describing the shipment, including shipment sourceand destination, freight carrier, freight tracking information, currentshipment status, shipment contents (by product type and number), date ofshipment, and the like).

In step 508, the scheduling module 304 updates the delivery commitmentmaterial and/or part and/or component and/or product schedulinginformation based on distribution chain performance or schedulinginformation, supply chain requirements, and/or projections.

In decision diamond 512, the scheduling module 304 compares the resultsof steps 504 and 508 and determines whether there is a product deliveryscheduling problem.

When there is a scheduling problem, the scheduling module 304, in step516, notifies the risk manager.

When no scheduling problem exists, the scheduling module 304 updates thedatabase and returns to step 500 to await the next stimulus instance.

FIG. 7 depicts operation of the analytical engine.

Upon detection of stimulus in step 500, the analytical engine, in step600, retrieves current performance data for each supply chain node.

In step 604, the analytical engine, for each tier 1 supply chain node orfacility, determines a likely product shipping and/or receipt date fromeach tier 2 node or facility.

In step 608, the analytical engine, using the results of step 604 andother data, determines, for each tier 2 supply chain node, a likelycomponent shipping and/or receipt date from each tier 3 node orfacility.

In step 612, the analytical engine, using the results of step 608 andother data, determines, for each tier 3 supply chain node, a likelycomponent shipping and/or receipt date from each tier 4 node orfacility.

In step 616, the analytical engine 312 compares the results of steps604, 608 and 612 and determines whether there is a material and/or partand/or component and/or product delivery scheduling problem at any tier.As will be appreciated, a material and/or part and/or component and/orproduct delivery scheduling problem is not limited to material and/orpart and/or component and/or product delivery shortfalls relative todistribution chain demands or requirements. A material and/or partand/or component and/or product delivery scheduling problem can alsoexist when too much product inventory is on hand at a tier 1 facility.In that event, supply chain requirements may need to be decreased todelay or reduce material and/or part and/or component and/or productdelivery. This determination can be made by comparing on-hand productinventory to distribution chain demands or requirements. When at least afirst threshold level but no more than a second threshold level ofinventory is on hand (after projected product delivery), a correctinventory level is present at a tier 1 facility. When more than thesecond threshold level of inventory is on hand (after projected productdelivery), an over-inventory condition exists and a modification to thesupply chain requirements is appropriate.

When there is a scheduling problem, the analytical engine, in step 620,notifies the risk manager.

When no scheduling problem exists, the analytical engine updates thedatabase and returns to step 500 to await the next stimulus instance.

FIG. 7 depicts the operation of the risk manager.

In step 700, the risk manager receives a stimulus. Stimuli include, forexample, a request from a tier 1 manager, a notification received fromthe analytical engine, passage of time, and the like. When necessary,the risk manager queries the analytical engine for an analysis ofperformance information.

In step 704, the risk manager retrieves the appropriate rule or policyset or template from the database.

In step 708, the risk manager determines, based on a comparison of thematerial and/or part and/or component and/or product delivery schedulingproblem with the appropriate rule or policy set or template, anappropriate action to be taken.

A first appropriate action 712 is to notify tier 1 management of thematerial and/or part and/or component and/or product delivery schedulingproblem.

A second appropriate action 716 is to notify management of each of theresponsible lower tier node(s) of the product delivery schedulingproblem and request a proposed mitigation measure to obviate thematerial and/or part and/or component and/or product delivery schedulingproblem.

A third appropriate action 720 is to identify an alternate lower tiernode(s) to resolve the material and/or part and/or component and/orproduct delivery scheduling problem and/or query an alternative node(s)for availability in assisting in mitigating and/or rectifying thematerial and/or part and/or component and/or product delivery schedulingproblem. For example, an alternative facility of a tier partner can bequeried to assist in increasing or decreasing production to mitigateand/or rectify the product delivery scheduling problem at a companionfacility of the tier partner. An alternative tier partner can be queriedto assist in increasing or decreasing production to mitigate and/orrectify the material and/or part and/or component and/or productdelivery scheduling problem at a competitive tier partner.

Other appropriate action(s) 724 include providing a recommendation totier 1 management of mitigation measure(s) to address and/or rectify thematerial and/or part and/or component and/or product delivery schedulingproblem, a combination of any of the foregoing actions, ship on-handproduct inventory from a different tier 1 facility to the demand chainpartner, and the like.

Multi-Supply Chain Management System

With reference to FIG. 8, a multi-supply chain management system 800 isdepicted. The system 800 includes first, second, . . . xth communicationdevices 804 a-x, shipment enterprise and/or organization server(s) 250,supply chain server(s) 808, the accessible information source(s) 812,shipment enterprise and/or organization server 250, and supply chainmanagement platform 816, interconnected by the wide area network 228.

The first, second, . . . xth communication devices 804 a-x can bepersonal communication devices, such as laptops, personal computers,tablet computers, personal digital assistants, and cellular phones,and/or enterprise or organization communication devices, such asservers.

The supply chain server(s) correspond to multiple different andindependent supply chains. Each supply chain includes, with reference toFIG. 1, a tier 1 control tower 100 and accompanying server 204, tier 2assembler 104 and accompanying server 212, first, second, . . . nth tier3 part/component manufacturer 108 a-n and accompanying servers 216 a-n,and first, second, third, . . . mth tier 4 material supplier 112 a-m andaccompanying servers 220 a-m.

The supply chain management platform 816 comprises not only the datacollection module 300, risk manager 316, scheduling module 304,reporting module 320, analytical engine 312, and historical state module308 but also a gateway 820, application programming interface(s) 824(one of which typically corresponds to each of the data collectionmodule 300, risk manager 316, scheduling module 304, reporting module320, analytical engine 312, and historical state module 308), securitymodule 828, and pricing monitoring module 850. All of the components areinterconnected by a trusted local area network 832.

The gateway 820 is a network point (e.g., a router) that acts as anentrance to the local area network 832. The gateway node can also act asa proxy server and/or a firewall to provide security to the local areanetwork 832.

The application programming interface(s) 824 define or specify howsoftware components interact with one another. Typically, each API is alibrary that includes specification for routines, data structures,object classes, and variables. The API may be implemented in aprocedural language or object-oriented language. An API specificationcan take many forms, including an International Standard such as POSIX,vendor documentation such as the Microsoft Windows™ API and/or thelibraries of a programming language, e.g., Standard Template Library inC++ or Java API. An API differs from an application binary interface(ABI) in that an API is source code based while an ABI is a binaryinterface. The data collection module 300, risk manager 316, schedulingmodule 304, reporting module 320, analytical engine 312, and historicalstate module 308 commonly use a common API or different APIs that areconfigured substantially the same. Generally, all internal and externalsignaling, including inter-application, intra-application, and/orinter-device messages, pass through APIs.

The security module 828 enforces access privileges and thereby maintainsdata security for each enterprise, organization, and supply chain. Thiscan be important as supply chains of competitors may be simultaneouslyusing the platform 816 for supply chain management.

The security module 828 can employ a variety of techniques.

One technique is application-based, which determines whether the userhas permission to access one or more of the data collection module 300,risk manager 316, scheduling module 304, reporting module 320,analytical engine 312, and historical state module 308. This can bedetermined using licensing techniques, whereby the user is subjected toaccess and/or feature restrictions depending on payments made to theplatform operator.

Another technique is API-based, which determines whether the user haspermission to access one or more of the APIs. Although the user may belicensed to use an application, he or she may not be licensed orprivileged to use one or more APIs within that application. Permissioncan also be determined using licensing techniques, whereby the user issubjected to access and/or feature restrictions depending on paymentsmade to the platform operator, or enforcement of privileges. The query,command, and/or request is typically further required to conform to therequirements of the application programming interface and, when thequery, command, and/or request fails to conform to the requirements ofthe application programming interface, the security module can deny thequery, command, and/or request even though the requestor has permissionto use the API.

Another technique is data entity or role-based, whereby specified rolescan create, read, update, and delete specified objects. For example, asystem 816 administrator role can create, read, update and deleteenterprise and/or organization, administrator, organization, site, item,and user objects. An administrator for an enterprise and/or organizationin a particular supply chain, by contrast, can create, read, update, anddelete administrators, users, organizations, sites, and items but onlyfor the particular enterprise and organization. An event manager for anenterprise and/or organization can create site, item, item-siterelationships, item-item relationships, and supply chain events but onlyfor the particular enterprise and organization.

Yet another technique is field level-based, which determines whether ornot the user has permission to view or change the field. This techniquecan also be role-based.

In either of the data entity or field level-based techniques, dataobjects can have different states (e.g., a purchase order can havedifferent states) and be viewed as state machines, whereby a state of adata object is changed by an action. Stated another way, actions causetransitions between states. Each state has a collection of actions thatare allowed and permissions associated with performing an action. Statescan have sub-states for a particular role type. For example, a sellermay have a requirement to approve a sell price by a manager beforecommitting the order. Basically, all actions can update an artifactexcept the first one (create). When an update or delete request isreceived, the security module or API checks the permissions for thestate. When permitted, the update is executed and the the artifactassigned a next state or the artifact deleted.

Yet another technique is to control the structure of, or restructure,database queries, commands or requests to comply with relevant sets ofpermissions. A requestor can write any database query, command, orrequest desired. The security module receives and applies a securitydefinition to the query, command, or request. If required, the securitymodule edits the query, command, or request consistent with the securitydefinition. The revised or restructured query, command, or request isthen passed onto the API of the data collection module. By way ofexample, assume that there are two supply chains, with the tier 1control tower on one supply chain being associated with Hewlett Packard™laptops and the tier 1 control tower on the other supply chain beingassociated with Dell™ laptops. They each share a common tier 3 componentmanufacturer, namely Intel™, which supplies integrated circuit boards toeach supply chain. A Dell employee provides the following query to theplatform 800:

Q: Select * from order where Seller=* and Buyer=*, where “*” is awildcard. This query, if executed, would provide the Dell™ employee withall rows and fields in both the Hewlett Packard™ and Dell™ supplychains. To provide the Dell employee with the supply chain informationto which he or she is entitled, the security module can restructure thequery as follows:

Q: Select * from order where Seller=Dell or Buyer=Dell. This queryprovides the requestor with only rows and fields in which Dell is eitherseller or buyer. Because Intel™ is common to both supply chains, thefollowing query “Q:Select * from order where Seller=Intel or Buyer=Intelwill retrieve rows and fields from both supply chains in which Intel iseither seller or buyer. In this manner, the security module canimplement both row-based and field-based access restrictions, in areadily scalable format, without requiring users associated withenterprises and organizations in the supply chain to voluntarilyrestrict database queries, commands, and requests in accordance with aparticular grammar or language.

While the security module is discussed with reference to informationinvolving only a particular enterprise or organization, it is to beunderstood that the enterprises and organizations within a supply chaincan agree to provide information to other enterprises and organizationslocated upstream of downstream in the supply chain, such as to the tier1 control tower. In such cases, the security definition takes suchexpanded information access into consideration.

The security module can enable the collected information to bemaintained in one data location (and common database) without the use ofa partitioned database. In other words, the database is not partitionedlogically (horizontally or vertically) into distinct and independentparts corresponding to different monitored supply chains, and the dataand/or data structures for different monitored supply chains can becommingled and/or conform to a common data model in the database. Thiscan enable the use of a simpler data model that enables ease ofconstructing relationships between enterprises and organizations,provide stability, and provide scalability. Each data row of the modelcan have a different schema. The data model can also enable sharing ofinformation across and among different supply chains.

The pricing monitoring module 850 monitors long term contract and spotmarket prices on materials and/or parts and/or components and/orproducts and generates alarms or notifications when the monitored priceschange upwards or downwards beyond specified thresholds. This can bedone effectively by identifying all materials and/or parts and/orcomponents within a selected product. For example, a bill of materialscan provide visibility into the various materials and/or parts and/orcomponents of a selected product. An integrated circuit board, forinstance, includes a broad number of raw materials, such as silicon,dopants, conductive metals for traces and other conductive structures,and device subcomponents, such as microprocessors, memory modules, etc.,and is itself a device used in many end products. The pricing module 850would monitor prices not only for the raw materials but also for thesubcomponents and the device itself. Sudden changes in raw materialsprices can provide an advance indication of price changes in the device.This can be used by the pricing monitoring module 850 not only toestimate the resulting device price but also indicate to administratorsthat additional inventory of the device should be acquired before theprice changes. An example of a price estimation algorithm is todetermine how much of the raw material is used in the device and the nettotal increase in cost for the device manufacturer. This net costincrease can be added to the current price to provide a fairly reliablecost estimate.

The analytical engine 320 can also calculate and update performancemeasures as information is collected by the data collection module 300.In other words, the calculation and updating of performance measures isdone substantially in real time. Alternatively, the analytical engine320 can calculate the performance measures when and as requested by auser. In other words, the performance measures are not precalculated.This can obviate the need for an analytics database altogether.

Operation of the Security Module 828

With reference to FIG. 9, the operation of the security module 828 willbe discussed.

In step 900, the supply chain management platform 816 receives an accessrequest, such as a query, command, or request. The access request can befrom a platform administrator or user or from an administrator or memberof an enterprise or organization in a supply chain monitored by theplatform 816 (hereinafter “requestor”).

The security process begins in decision diamond 904, in which thesecurity module 828 determines whether the requestor has permission touse the application to which the access request is directed and the APIassociated with the application or function or feature of theapplication to process the access request.

When the requestor has permission to use the application and API, thesecurity module 828, in decision diamond 908, determines whether therequestor is privileged to interact with the data entity. As noted, thisquery determines whether the requestor has a specified role privilegedto create, read, update, and delete the specified data object.

When the requestor does not have permission to use either theapplication or the specific API of the application involved inprocessing the access request or is not privileged to interact with thedata entity or object, the security module 828 proceeds to step 928 anddenies the request.

When the requestor is privileged to interact with the data entity orobject, the security module 828 proceeds to step 912 and applies asecurity definition to the access request and, if required, edits orreconfigures the access request consistent with the applied securitydefinition.

In step 916, the security module 828 forwards the edited request to theapplication, e.g., the data collection module 300, risk manager 316,scheduling module 304, reporting module 320, analytical engine 312,and/or historical state module 308, for processing.

In optional step 920, the security module 828 receives the response andfilters out any information that the requestor is not privileged toaccess. This is a precautionary step in the event that a database errorhas caused information to be retrieved improperly.

In step 924, the security module 828 routes the response to therequestor optionally through the appropriate API.

Operation of the Pricing Monitoring Module 850

The operation of the pricing monitoring module 850 will now be discussedwith reference to FIG. 10.

In step 1000, the pricing monitoring module 850 detects a stimulus. Thestimulus can be, for example, expiration of a selected time period.

In step 1004, the pricing monitoring module 850 selects a next productfor consideration. This step can be done on a supply chain-by-supplychain basis and, for a given supply chain, for one or more selectedenterprises or organizations within the supply chain. For example andwith reference to FIG. 1, the product can be a product sold by one ormore of a tier 1 control tower server 204, tier 2 assembler server 212,first, second, . . . nth tier 3 component manufacturer server 216 a-n,and first, second, third, . . . mth tier 4 material supplier server 220a-m.

In step 1008, the pricing monitoring module 850 selects a nextcomponent(I) of the selected product. As noted, the component can be araw or processed material, formulation, device, or other component.

In step 1012, the pricing monitoring module 850 determines a currentpricing information for the selected component. This is typically doneusing one or more accessible information source(s) 224, such as bybrowsing the Web.

In decision diamond 1016, the pricing monitoring module 850 determineswhether the current pricing information for the selected componentdiffers materially from a previously determined or currently realizedpricing for the component. “Materially” is typically determined by oneor more thresholds. If the price rises or falls in excess of apredetermined threshold, the pricing change is deemed to be material.

When a price change is material, the pricing monitoring module 850, instep 1020, generates an alarm and/or notification to an administrator ofthe pertinent enterprise and/or organization.

In decision diamond 1024, the pricing monitoring module 850 determineswhether all components for the selected product have been considered.

When there is no material pricing change (decision diamond 1016) or allcomponents have not been considered, the pricing monitoring module 850returns to step 1008 and selects a next component for pricing analysis.

When all components have been considered, the pricing monitoring module850, in step 1028, determines a new price for the selected product.

The pricing monitoring module 850 then returns to step 1004 and selectsa next product for analysis.

The pricing monitoring module 850 and analytical engine can determine afinancial impact on a supplier of the product and/or downstream user ofthe product. The financial impact analysis can be done for the selectedproduct or across all product lines of the supplier and/or downstreamuser and/or for the supply chain as a whole.

The exemplary systems and methods of this disclosure have been describedin relation to a computer network. However, to avoid unnecessarilyobscuring the present disclosure, the preceding description omits anumber of known structures and devices. This omission is not to beconstrued as a limitation of the scopes of the claims. Specific detailsare set forth to provide an understanding of the present disclosure. Itshould however be appreciated that the present disclosure may bepracticed in a variety of ways beyond the specific detail set forthherein.

Furthermore, while the exemplary aspects, embodiments, and/orconfigurations illustrated herein show the various components of thesystem collocated, certain components of the system can be locatedremotely, at distant portions of a distributed network, such as a LANand/or the Internet, or within a dedicated system. Thus, it should beappreciated, that the components of the system can be combined in to oneor more devices, such as a server, or collocated on a particular node ofa distributed network, such as an analog and/or digitaltelecommunications network, a packet-switch network, or acircuit-switched network. It will be appreciated from the precedingdescription, and for reasons of computational efficiency, that thecomponents of the system can be arranged at any location within adistributed network of components without affecting the operation of thesystem. For example, the various components can be located in a switchsuch as a PBX and media server, gateway, in one or more communicationsdevices, at one or more users' premises, or some combination thereof.Similarly, one or more functional portions of the system could bedistributed between a telecommunications device(s) and an associatedcomputing device.

Furthermore, it should be appreciated that the various links connectingthe elements can be wired or wireless links, or any combination thereof,or any other known or later developed element(s) that is capable ofsupplying and/or communicating data to and from the connected elements.These wired or wireless links can also be secure links and may becapable of communicating encrypted information. Transmission media usedas links, for example, can be any suitable carrier for electricalsignals, including coaxial cables, copper wire and fiber optics, and maytake the form of acoustic or light waves, such as those generated duringradio-wave and infra-red data communications.

Also, while the flowcharts have been discussed and illustrated inrelation to a particular sequence of events, it should be appreciatedthat changes, additions, and omissions to this sequence can occurwithout materially affecting the operation of the disclosed embodiments,configuration, and aspects.

A number of variations and modifications of the disclosure can be used.It would be possible to provide for some features of the disclosurewithout providing others.

For example in one alternative embodiment, the techniques discussedherein are applied to animate objects, such as processing people,particularly at a check point. The Department of Homeland Security canuse the management systems to process people more effectively at airportsecurity checkpoints and the Immigration and Naturalization Service canuse the management systems to process more effectively at bordercrossings.

In another alternative embodiment, the techniques discussed herein canbe applied to inanimate objects, such as mail or packages, such as by apostal, courier or freight service.

In yet another embodiment, the systems and methods of this disclosurecan be implemented in conjunction with a special purpose computer, aprogrammed microprocessor or microcontroller and peripheral integratedcircuit element(s), an ASIC or other integrated circuit, a digitalsignal processor, a hard-wired electronic or logic circuit such asdiscrete element circuit, a programmable logic device or gate array suchas PLD, PLA, FPGA, PAL, special purpose computer, any comparable means,or the like. In general, any device(s) or means capable of implementingthe methodology illustrated herein can be used to implement the variousaspects of this disclosure. Exemplary hardware that can be used for thedisclosed embodiments, configurations and aspects includes computers,handheld devices, telephones (e.g., cellular, Internet enabled, digital,analog, hybrids, and others), and other hardware known in the art. Someof these devices include processors (e.g., a single or multiplemicroprocessors), memory, nonvolatile storage, input devices, and outputdevices. Furthermore, alternative software implementations including,but not limited to, distributed processing or component/objectdistributed processing, parallel processing, or virtual machineprocessing can also be constructed to implement the methods describedherein.

In yet another embodiment, the disclosed methods may be readilyimplemented in conjunction with software using object or object-orientedsoftware development environments that provide portable source code thatcan be used on a variety of computer or workstation platforms.Alternatively, the disclosed system may be implemented partially orfully in hardware using standard logic circuits or VLSI design. Whethersoftware or hardware is used to implement the systems in accordance withthis disclosure is dependent on the speed and/or efficiency requirementsof the system, the particular function, and the particular software orhardware systems or microprocessor or microcomputer systems beingutilized.

In yet another embodiment, the disclosed methods may be partiallyimplemented in software that can be stored on a storage medium, executedon programmed general-purpose computer with the cooperation of acontroller and memory, a special purpose computer, a microprocessor, orthe like. In these instances, the systems and methods of this disclosurecan be implemented as program embedded on personal computer such as anapplet, JAVA® or CGI script, as a resource residing on a server orcomputer workstation, as a routine embedded in a dedicated measurementsystem, system component, or the like. The system can also beimplemented by physically incorporating the system and/or method into asoftware and/or hardware system.

Although the present disclosure describes components and functionsimplemented in the aspects, embodiments, and/or configurations withreference to particular standards and protocols, the aspects,embodiments, and/or configurations are not limited to such standards andprotocols. Other similar standards and protocols not mentioned hereinare in existence and are considered to be included in the presentdisclosure. Moreover, the standards and protocols mentioned herein andother similar standards and protocols not mentioned herein areperiodically superseded by faster or more effective equivalents havingessentially the same functions. Such replacement standards and protocolshaving the same functions are considered equivalents included in thepresent disclosure.

The present disclosure, in various aspects, embodiments, and/orconfigurations, includes components, methods, processes, systems and/orapparatus substantially as depicted and described herein, includingvarious aspects, embodiments, configurations embodiments,subcombinations, and/or subsets thereof. Those of skill in the art willunderstand how to make and use the disclosed aspects, embodiments,and/or configurations after understanding the present disclosure. Thepresent disclosure, in various aspects, embodiments, and/orconfigurations, includes providing devices and processes in the absenceof items not depicted and/or described herein or in various aspects,embodiments, and/or configurations hereof, including in the absence ofsuch items as may have been used in previous devices or processes, e.g.,for improving performance, achieving ease and\or reducing cost ofimplementation.

The foregoing discussion has been presented for purposes of illustrationand description. The foregoing is not intended to limit the disclosureto the form or forms disclosed herein. In the foregoing DetailedDescription for example, various features of the disclosure are groupedtogether in one or more aspects, embodiments, and/or configurations forthe purpose of streamlining the disclosure. The features of the aspects,embodiments, and/or configurations of the disclosure may be combined inalternate aspects, embodiments, and/or configurations other than thosediscussed above. This method of disclosure is not to be interpreted asreflecting an intention that the claims require more features than areexpressly recited in each claim. Rather, as the following claimsreflect, inventive aspects lie in less than all features of a singleforegoing disclosed aspect, embodiment, and/or configuration. Thus, thefollowing claims are hereby incorporated into this Detailed Description,with each claim standing on its own as a separate preferred embodimentof the disclosure.

Moreover, though the description has included description of one or moreaspects, embodiments, and/or configurations and certain variations andmodifications, other variations, combinations, and modifications arewithin the scope of the disclosure, e.g., as may be within the skill andknowledge of those in the art, after understanding the presentdisclosure. It is intended to obtain rights which include alternativeaspects, embodiments, and/or configurations to the extent permitted,including alternate, interchangeable and/or equivalent structures,functions, ranges or steps to those claimed, whether or not suchalternate, interchangeable and/or equivalent structures, functions,ranges or steps are disclosed herein, and without intending to publiclydedicate any patentable subject matter.

What is claimed is:
 1. A system for monitoring multiple supply chainsfor different products, performance information collected for eachmonitored supply chain being confidential to the respective monitoredsupply chain and being stored in a common database, comprising: amicroprocessor executable security module operable to receive a query,command and/or request from a requestor to perform an operation withrespect to a set of data and/or data structures in the database, modifythe query, command and/or request to conform to a security definition,and use the modified query, command and/or request to perform theoperation.
 2. The system of claim 1, wherein the database is notpartitioned logically into distinct and independent parts correspondingto different monitored supply chains and wherein the data and/or datastructures for different monitored supply chains are commingled in thedatabase.
 3. The system of claim 1, wherein the query, command and/orrequest is modified by the security module to reflect a supply chainrole and/or an identity of an enterprise and/or organization associatedwith the requestor, whereby the data and/or data structures impacted bythe query, command, and/or request are limited to those relating to thesupply chain role and/or identity of the enterprise and/or organizationassociated with the requestor.
 4. The system of claim 1, wherein thesecurity module determines whether the requestor has permission to usean application associated with the operation and, when the requestor iswithout permission to use the application, denies the query, command,and/or request.
 5. The system of claim 1, wherein the query, command,and/or request is required to pass through an application programminginterface prior to performance of the operation and wherein the securitymodule determines whether the requestor has permission to use theapplication programming interface and/or whether the query, commandand/or request conforms to the requirements of the applicationprogramming interface and, when the requestor is without permission touse the application programming interface and/or when the query,command, and/or request fails to conform to the requirements of theapplication programming interface, denies the query, command, and/orrequest.
 6. The system of claim 1, wherein the requestor is required tohave a specified role and relationship to a selected monitored supplychain enterprise and/or organization before the operation can beperformed.
 7. The system of claim 1, wherein a datum and/or datumstructure of the set of data and/or data structures has differentstates, wherein an action must be performed to change the state of thedatum and/or datum structure, wherein each action can only be performedwhen the requestor has a permission to perform the action, and whereinone of the different states has plural sub-states that must be performedbefore the state can change.
 8. The system of claim 1, wherein supplychain performance metrics are not calculated, in substantial real time,based on the performance information collected from the monitored supplychains.
 9. A method, comprising: monitoring multiple supply chains fordifferent products, performance information collected for each monitoredsupply chain being confidential to the respective monitored supply chainand stored in a common database; a microprocessor executable securitymodule receiving a query, command and/or request from a requestor toperform an operation with respect to a set of data and/or datastructures in the database; the security module modifying the query,command and/or request to conform to a security definition; and thesecurity module using the modified query, command and/or request toperform the operation.
 10. The method of claim 9, wherein the databaseis not partitioned logically into distinct and independent partscorresponding to different monitored supply chains and wherein the dataand/or data structures for different monitored supply chains arecommingled in the database.
 11. The method of claim 9, wherein thequery, command and/or request is modified by the security module toreflect a supply chain role and/or an identity of an enterprise and/ororganization associated with the requestor, whereby the data and/or datastructures impacted by the query, command, and/or request are limited tothose relating to the supply chain role and/or identity of theenterprise and/or organization associated with the requestor.
 12. Themethod of claim 9, wherein the security module determines whether therequestor has permission to use an application associated with theoperation and, when the requestor is without permission to use theapplication, denies the query, command, and/or request.
 13. The methodof claim 9, wherein the query, command, and/or request is required topass through an application programming interface prior to performanceof the operation and wherein the security module determines whether therequestor has permission to use the application programming interfaceand/or whether the query, command and/or request conforms to therequirements of the application programming interface and, when therequestor is without permission to use the application programminginterface and/or when the query, command, and/or request fails toconform to the requirements of the application programming interface,denies the query, command, and/or request.
 14. The method of claim 9,wherein the requestor is required to have a specified role andrelationship to a selected monitored supply chain enterprise and/ororganization before the operation can be performed.
 15. The method ofclaim 9, wherein a datum and/or datum structure of the set of dataand/or data structures has different states, wherein an action must beperformed to change the state of the datum and/or datum structure,wherein each action can only be performed when the requestor has apermission to perform the action, and wherein one of the differentstates has plural sub-states that must be performed before the state canchange.
 16. The method of claim 9, wherein supply chain performancemetrics are not calculated, in substantial real time, based on theperformance information collected from the monitored supply chains. 17.A tangible and non-transient computer readable medium comprisingmicroprocessor executable instructions that, when executed, performtasks comprising: monitoring multiple supply chains for differentproducts, performance information collected for each monitored supplychain being confidential to the respective monitored supply chain andstored in a common database; receive a query, command and/or requestfrom a requestor to perform an operation with respect to a set of dataand/or data structures in the database; modify the query, command and/orrequest to conform to a security definition; and use the modified query,command and/or request to perform the operation.
 18. The computerreadable medium of claim 17, wherein the database is not partitionedlogically into distinct and independent parts corresponding to differentmonitored supply chains and wherein the data and/or data structures fordifferent monitored supply chains are commingled in the database. 19.The computer readable medium of claim 17, wherein the query, commandand/or request is modified by the instructions to reflect a supply chainrole and/or an identity of an enterprise and/or organization associatedwith the requestor, whereby the data and/or data structures impacted bythe query, command, and/or request are limited to those relating to thesupply chain role and/or identity of the enterprise and/or organizationassociated with the requestor.
 20. The computer readable medium of claim17, wherein the instructions determine whether the requestor haspermission to use an application associated with the operation and, whenthe requestor is without permission to use the application, denies thequery, command, and/or request.
 21. The computer readable medium ofclaim 17, wherein the query, command, and/or request is required to passthrough an application programming interface prior to performance of theoperation and wherein the instructions determine whether the requestorhas permission to use the application programming interface and/orwhether the query, command and/or request conforms to the requirementsof the application programming interface and, when the requestor iswithout permission to use the application programming interface and/orwhen the query, command, and/or request fails to conform to therequirements of the application programming interface, denies the query,command, and/or request.
 22. The computer readable medium of claim 17,wherein the requestor is required to have a specified role andrelationship to a selected monitored supply chain enterprise and/ororganization before the operation can be performed.
 23. The computerreadable medium of claim 17, wherein a datum and/or datum structure ofthe set of data and/or data structures has different states, wherein anaction must be performed to change the state of the datum and/or datumstructure, wherein each action can only be performed when the requestorhas a permission to perform the action, and wherein one of the differentstates has plural sub-states that must be performed before the state canchange.
 24. The computer readable medium of claim 17, wherein supplychain performance metrics are not calculated, in substantial real time,based on the performance information collected from the monitored supplychains.